Controlling device output according to a determined condition of a user

ABSTRACT

Dynamically controlling output from a device, such as an automated assistant device. Control of the output can be based on, for example, a condition and/or physiological attribute(s) of a user of the device. Various implementations dynamically control the output to improve sleep quality for the user and/or mitigate waste of computational and/or network resources.

BACKGROUND

Sleep quality can be pivotal to maintaining a healthy mind as one ages.Oftentimes, environmental elements that affect sleep quality can includeother persons, abrupt environmental noises, and/or other subjectivesensitivities that a person may have. Although there are some devicesavailable to assist a person in falling asleep, such devices may operateinefficiently and cause incidental sleep disturbances. For instance,some white noise machines have set timers and may provide white noise ata constant level, even when a user has already fallen asleep. Should theuser set the timer for a period that extends past a time they wouldeventually fall asleep, the white noise machine will continue providingaudio at the constant level despite the user falling asleep, therebywasting energy and computational resources. Furthermore, should the userset the timer for a period that falls short of a time when the user hasinitially fallen asleep, a sudden stoppage of the white noise can causea sleep disturbance, thereby waking the user. As a result, the user maywake up and reinitialize the timer for the white noise machine, whichcan lead to additional energy and computational resources being expendedon extending operations of the white noise machine, at least compared toa scenario where the user had remained asleep.

Similarly, a user that typically employs a computing device for playingan audiobook until they fall asleep may inadvertently cause thecomputing device to operate inefficiently as a result of using standardtimers for stopping the audiobook once the user has fallen asleep. Forinstance, a user may set a timer for an audiobook to play for one hourwhile the user is falling asleep. Should the user fall asleep prior tothe timer going off, the audiobook will continue to play at a maintainedvolume level until the timer going off, thereby wasting computationalresources required to continue to play the audiobook at the maintainedvolume level. Further, the user will not comprehend a portion of theaudio book should the user fall asleep prior to the timer going off. Asa result, the next time the user initializes the audiobook, they wouldhave to scroll (or otherwise navigate) through a variety of portions ofthe audiobook in order to identify where they left off prior to fallingasleep. This can waste computational resources, as memory would berequired to buffer previews of certain portions of the audiobook, andprocessor resources would be required to cause playback of the audiobookuntil the user identifies where they left off.

Other devices that operate according to whether a user is awake orasleep, such as a motion activated device, can also waste resources whenan operating mode of the device is not particularly efficient in view ofa state of the user. For instance, in a household where multiple peopleare sleeping, a single user may get up from their bed in order to have adrink of water or use the restroom. Should a motion sensor trigger alight to emit white light in response, energy required to illuminate thelight may be wasted—as the user may not need a full spectrum of light tonavigate from their bedroom to a kitchen or a bathroom. Furthermore,white light may be disturbing to any other person that remains asleepwhile the user is moving about. In some instances, such a response by amotion detector can invoke a “domino effect” of devices reacting to apresence of the user, despite the user only intending to take a smallbreak from sleeping and return to bed. In such instances, any ancillarydevices reacting to a presence of the user may inadvertently waste powerand computational resources in responding to the actions taken by theuser.

SUMMARY

The present disclosure is generally directed to methods, apparatus, andcomputer-readable media (transitory and non-transitory) for improvingsleep quality for a user while simultaneously mitigating waste ofcomputational and/or network resources. In various implementations, acondition and/or physiological attribute(s) of the user can bedetermined, with permission of the user, in order to determine how toeffectively control one or more devices, such as an ambient noisegenerator and/or other computing device (e.g., a computing devicedevoted to automated assistant functions), to improve sleep quality forthe user and/or mitigate waste of computational and/or networkresources. For example, the user can have one or more assistant devicescapable of responding to spoken utterances from the user, and alsoproviding various outputs via one or more different modalities to assista user with sleeping. The user can provide a spoken utterance such as,“Assistant, please play ambient sounds until I fall asleep.” Inresponse, and with approval of the user (e.g., previously grantedapproval), an automated assistant associated with the assistant devicescan access data that characterizes a condition of the user and/or aprevious condition of the user. For instance, the data can characterizethe user as having just laid down to go to sleep immediately prior toproviding the spoken utterance, and the automated assistant can, basedon the data, characterize the user as being in a first condition.

The data can be based on outputs from one or more different computingdevices that are in communication with the automated assistant. Forinstance, the data can be based on an output of a smart watch or otherwearable device that the user is wearing when they are lying in theirbed. The wearable device can include one or more sensors configured tobe responsive to one or more different physiological attributes of theuser, such as heart rate, blood pressure, oxygen level, respiratoryrate, motion and/or twitch, and/or any other attribute that can indicatea condition of the person. Additionally, or alternatively, the data canbe based on an output of one or more devices not being worn by the user,such as a motion sensor, a vision sensor (e.g., a camera), a standalonespeaker device, a portable computing device such as, but not limited to,a tablet or cellular phone, and/or any other device capable of providingan output that indicates a condition of the user. For example, the datacan be based on output from an application of a computing device, andthe output can characterize a schedule of the user, thereby indicatingwhen the user is no longer scheduled to be engaged in any certainactivities.

The data can be processed to determine one or more outputcharacteristics that would be suitable for promoting the user fallingasleep. In other words, one more characteristics or settings for anoutput being rendered by a computing device can be identified for:reducing a probability that the user will regress away from being asleepwhen the user is receiving the output; and/or reducing a probabilitythat an amount of time for the user to fall asleep will increase inresponse to the output having the one or more characteristics orsettings when the user is receiving the output. Furthermore, thecharacteristics can be adjusted for any condition, including when theuser is asleep or predicted to be asleep. In this way, thecharacteristics can continually be made suitable for ensuring the useris progressing toward falling asleep and staying asleep—at least duringa period in which the user would prefer to be asleep.

For instance, when the user is in a first condition, such as, but notlimited to, the user having just entered their bed to lie down, acharacteristic such as volume can be selected for an ambient sound to beemitted by a computing device. When it is determined (e.g., based on acondition of the user, which can include sensed physiological attributesof the user, circumstantial attributes that can be external to the user,and/or circumstantial data that can be associated with the user) thatthe user is transitioning from the first condition to a secondcondition, such as, but not limited to, one in which the user has ahigher probability of falling asleep, the characteristic can be adjustedin response. For example, a characteristic such as volume can beselected as a lower volume compared to a volume that was selected whenthe user was in the first condition. In this way, as the user graduallyprogresses closer to falling asleep or inadvertently away from stayingasleep, one or more characteristics of the output being perceived by theuser can be adjusted accordingly. One or more additional or alternativecharacteristics that can be adjusted as the user transitions towardsfalling asleep, or inadvertently away from staying asleep, can includeequalization, reverb, tone, phase, frequency, brightness, temperature,and/or any other characteristic of an output modality that can beadjusted via a computing device.

In some implementations the user can be asleep, but regress fromsleeping into a second condition. The regression can be in response toan event or environmental factor, such as wind blowing outside, trafficnoises nearby, a spouse entering the home or getting up from bed, and/orany other action that can affect sleep of the user. An automatedassistant, or other application or device, can identify the action as adisturbance to the user, and/or detect that the user has been disturbed,and modify one or more characteristics of the output accordingly. Forexample, in response to detecting a sleep disturbance, or that the userhas regressed from sleep to the second condition, one or morecharacteristics of an output of a computing device can be adjusted inorder to promote the user progressing from the second condition back tosleeping. For instance, a volume of an output can be increased inresponse to detecting that the user has regressed from sleeping to thesecond condition, thereby distorting any incidental noises that mayoccur when the user is in the second condition. Should the user progressfrom the second condition back to sleeping, the one or morecharacteristics can again be adjusted in order to promote the userstaying asleep, or otherwise exhibiting a desired physiologicalattribute (e.g., exhibiting qualities of being at rest).

In some implementations, instead of requesting that ambient noise beplayed while the user is attempting to fall asleep, the user can requestthat the automated assistant stream or otherwise play other media, suchas an audiobook, a podcast, a movie, a television show, etc. The mediacan have a finite duration, which may extend beyond an amount of time ittakes for the user to transition to falling asleep. If the mediacontinues to be rendered beyond the user falling asleep and/or continuesto be rendered at the same volume and/or brightness, computationalresources and/or network resources can be wasted. However, according tosome implementations disclosed herein, a volume and/or brightness atwhich the media is rendered can be reduced responsive to determining theuser is asleep. As one non-limiting example, the volume can be reduced afirst amount upon determining that the user has initially fallen asleep,reduced a greater second amount upon determining that the user hasprogressed to a deeper state of sleep, and reduced an even greater thirdamount upon determining that the user has progressed to an even deeperstate of sleep. Additionally or alternatively, some implementations canhalt the playing of the media in response to determining the user hasprogressed to a certain state of sleep, or replace the rendering of themedia with rendering of ambient sounds.

When the user initially lies down, the automated assistant can determinethat the user is in a first condition. Data that is based on one moreoutputs generated when the user is in the first condition can beprocessed in order to determine whether the user is progressing towardsa second condition, such as falling asleep or entering a near sleepstate. When the user is determined to have transitioned from the firstcondition to the second condition, a time stamp can be identified as atemporal location within the audio data that corresponds to a time whenthe user entered the second condition. In this way, the user can returnto the identified temporal location the following day or otherwise whenthey wake up, without having to search through the audiobook for aportion of the audiobook that they heard last. This can preservecomputational resources, such as memory, which can be required when,absent a generated time stamp described herein, a user is previewingvarious portions of an audio file or an audio stream to discern whatportion of the audiobook they heard last.

In some implementations, a separate timestamp can be identified inresponse to the user transitioning to another condition (e.g., from anear sleep state to a sleep state), despite the automated assistantalready causing another timestamp to be generated. In other words, whenthe user transitions from the first condition to the second condition,the automated assistant can identify a first timestamp corresponding toa temporal location within some media playback when the usertransitioned into the second condition. Subsequently, when the automatedassistant determines that the user has transitioned from the secondcondition to being asleep, the automated assistant can cause the secondtimestamp to be identified. The second timestamp can correspond toanother temporal location within the media playback at which the usertransitioned from the second condition to sleeping when the mediaplayback was being output into an environment in which the user wasattempting to fall asleep. In this way, should the user subsequentlywant to resume playback of the media, the user can be presented with twodifferent options, based on the two timestamps, where each optioncorresponds to a different temporal location of the media. For example,the user can be presented with an option to resume playback from a firstlocation in which the user was in a near sleep state, or from a secondlocation in which the user fell asleep.

Moreover, in some implementations disclosed herein, one more shortcutsand/or time stamps can be generated for returning to a point in themedia at which the user fell asleep, entered a near sleep state, orotherwise transitioned into another condition. These shortcuts and/ortime stamps can be subsequently utilized to enable a subsequent playbackof the audiobook or podcast to start near or at the point in the media.As one example, the user can provide a spoken utterance to theirassistant device such as, “Assistant play my audiobook.” In response,the automated assistant can cause a computing device to playback and/orstream audio data corresponding to the audiobook, starting from a pointin the media that corresponds to a time stamp.

In some implementations, a modality (e.g., a light source) that isdifferent from an audio modality (e.g., a speaker) can be operatedaccording to a detected condition of a user in order to promote a usertransitioning to being, and/or staying, asleep. The modality can be, forexample, a light interface, such as a display panel and/or any othersource of light, which can be adjusted to provide differentcharacteristics (e.g., frequencies, brightness, temperature, colortemperature, etc.) of light according to a detected condition of theuser. The detected condition can be based on determined physiologicalattributes of the user, and/or determined circumstantial attributesand/or circumstantial data (e.g., IoT data, schedule data, vehicle data,and/or any other data that can characterize a current and/or previouscircumstance of the user) associated with the user. For instance, anautomated assistant can determine that the user has been asleep for atleast a threshold period of time. Subsequently, the automated assistantcan determine that the user has gotten up from their bed and/orotherwise moved across a portion of an environment in which they werepreviously asleep. In response to determining that the user has gottenup from their bed after falling asleep, the automated assistant cancause a light source within the environment to emit a low colortemperature of light. For example, initially the automated assistant cancause the light source to emit a red light at 5% of a maximum brightnesscapable of being output by the light source. Should the user leave theenvironment, for example, to use the bathroom, the automated assistantcan cause the light source to reduce the brightness output to 2% or 0%.Subsequently, when the user is detected within the environment again,and a time when the user enters the environment corresponds to a timewhen the user is typically trying to rest, the automated assistant cancause the brightness level to increase again, back to 5%. In this way,the user can be guided by the light as they move about the environmentshould they wake up in the middle of the night, without wasting energyby providing all frequencies of light, such as white light, and/orproviding a maximum brightness of light.

Furthermore, the light can be provided at a particular color temperatureand/or brightness according to a detected condition of the user. Forexample, if the user is getting up from being asleep in the morning, theautomated assistant can cause the light source to provide a cooler colortemperature output and/or a brighter output. This can be based on anassumption that the user has slept a sufficient amount of time, andcould therefore use the cooler light to help them wake up.Alternatively, or additionally, if the user is getting up from beingasleep in the middle of the night, the automated assistant can cause thelight source to provide a warmer color temperature output and/or a lowerbrightness output, relative to a brightness output that would be emittedin the morning. This can be based on an assumption that the user has nothad a sufficient amount of sleep, and therefore would likely attempt togo back to sleep upon returning to their bed. In this way, energy can bepreserved within the home of the user, at least because the automatedassistant would cause lights to emit light according to a condition ofthe user, rather than merely turning on with all frequencies of lightand/or full brightness whenever the user triggers the light.

In some implementations, a condition of the user can be used as a basisfor providing the user with responses according to certaincharacteristics. In other words, one or more characteristics, forresponsive outputs, can be selected in order to promote the user stayingin their current condition or progressing toward falling asleep. Forexample, when the user is determined to be asleep, but nonethelessunexpectedly provides a spoken utterance such as, “Assistant, turn onthe lights,” the automated assistant can cause the lights to turn on—butaccording to characteristics selected for the user being asleep.Specifically, the characteristics can include, for example, a 5% dimminglevel and/or a low color temperature (e.g., a red light). In someimplementations, when the user is determined to be in a secondcondition, such as, but not limited to, just before the user fallsasleep, and provides a spoken utterance such as, “Assistant, what timeis it,” the automated assistant can provide an audible responseaccording to characteristics selected for the second condition. Forinstance, the audible response can be provided at a lower volumecompared to a volume that would otherwise be selected if the user wasawake and/or in a second condition, such as, but not limited to, whenthe user is determined to be in a sleep state. In this way, variousmodalities of a computing device and/or a peripheral device can becontrolled according to a determined condition (e.g., physiologicalattribute(s) of the user and/or circumstantial attribute(s) of theuser).

In some implementations, when an automated assistant device is invoked,responsive to an invocation phrase (e.g., “Hey, Assistant”) or otherwise(e.g., responsive to a gesture), the automated assistant device canacknowledge that it has been invoked by rendering an ambient sound(e.g., birds chirping, ocean waves, waterfall, and/or any other suitableambient sound). The ambient sound can optionally continue to be renderedso long as the automated assistant device is invoked. For example, theambient sound can continue to be rendered so long as the automatedassistant device is performing certain processing of captured audio thatis only performed when invoked, such as transmission of the capturedaudio to a remote server for speech-to-text processing, or localspeech-to-text processing. In other words, instead of, or in additionto, the automated assistant device illuminating an LED or providingother visual output to indicate it has been invoked, the automatedassistant device can provide ambient noise or other sounds to indicateit has been invoked—and optionally to indicate it continues to beinvoked. This can be beneficial in various scenarios, such as when auser is attempting to sleep and has his/her eyes shut, when theautomated assistant device is not visible to the user, the user isvisually impaired, etc. In some implementations, the sound that isrendered by the automated assistant device when invoked, can optionallybe rendered in a manner that is based on sensed physiological attributesof the user and/or determined circumstantial attributes of the user. Forexample, if the user is in a near sleep state, the sound can be renderedat a first volume whereas if the user is in an awake state, the soundcan be rendered at a second louder volume.

In some implementations, the sound that is rendered by the automatedassistant device when invoked, can optionally be rendered according to avoice signature and/or voice identification of the user. For instance,when a first user provides an invocation phrase such as, “Assistant,”the automated assistant device can respond by playing a sound of birdschirping in order to indicate to the first user that the automatedassistant device is anticipating a spoken utterance from the first user.Additionally, when a second user provides the invocation phrase, theautomated assistant device can respond by playing a sound of ocean wavesin order to indicate that the automated assistant is anticipating aspoken utterance from the second user. Additionally, or alternatively,the sound that is rendered by the automated assistant device wheninvoked, can optionally be rendered based on detected ambient sound,background noise, a distance of a user from the automated assistantdevice, and/or any other indicators that can be associated with sleepstate of a user. For instance, in some implementations a sound rendered,specifically for responding to the first user or the second user, canhave one or more characteristics that can be modified according todetected ambient sound, background noise, a distance of a user from theautomated assistant device, and/or any other indicators that can beassociated with sleep state of a user. For example, one or more valuesof characteristics such as volume, equalization, tone, reverb, delay,and/or any other sound feature can be adjusted. In this way, should thefirst user attempt to invoke the automated assistant when there is someamount of detected background noise, the sound of birds chirping canhave a volume value that is based on a volume of the detected backgroundnoise.

The above description is provided as an overview of some implementationsof the present disclosure. Further description of those implementations,and other implementations, are described in more detail below.

Other implementations may include a non-transitory computer readablestorage medium storing instructions executable by one or more processors(e.g., central processing unit(s) (CPU(s)), graphics processing unit(s)(GPU(s)), and/or tensor processing unit(s) (TPU(s)) to perform a methodsuch as one or more of the methods described above and/or elsewhereherein. Yet other implementations may include a system of one or morecomputers and/or one or more robots that include one or more processorsoperable to execute stored instructions to perform a method such as oneor more of the methods described above and/or elsewhere herein.

It should be appreciated that all combinations of the foregoing conceptsand additional concepts described in greater detail herein arecontemplated as being part of the subject matter disclosed herein. Forexample, all combinations of claimed subject matter appearing at the endof this disclosure are contemplated as being part of the subject matterdisclosed herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A and FIG. 1B illustrates perspective view of a first computingdevice modifying a particular output according to a condition of a user.

FIG. 2A and FIG. 2B illustrate perspective views of one or moretimestamps being generated according to a condition of a user when theuser is listening to, or otherwise perceiving, an output of a computingdevice.

FIG. 3A and FIG. 3B illustrate views of implementations wherein one ormore output of one or more computing devices can be modified in responseto a user regressing from a sleep state or other desired physiologicalstate, to a different state.

FIG. 4 illustrates a system for modifying one or more characteristics ofan output of a computing device and/or automated assistant according toa condition of a user, for example, in order to assist the user withfalling asleep.

FIG. 5 illustrates a method for identifying timestamps corresponding toa temporal location within of an output that a user transitioned betweenconditions and/or fell asleep.

FIG. 6 illustrates a method for modifying an output of a computingdevice according to a condition of a user.

FIG. 7 is a block diagram of an example computer system.

DETAILED DESCRIPTION

FIG. 1A and FIG. 1B illustrates perspective view 100 and a perspectiveview 102, respectively, of a first computing device 106 modifying aparticular output according to a condition of a user 104. Specifically,as the first computing device 106 determines that the user 104 isprogressing toward a sleep state, the first computing device 106 canmodify one or more characteristics of the output in order to promote orencourage the user 104 progressing toward the sleep state and/or stayingin the sleep state. Initially, the user 104 can be watching a movie viathe first computing device 106, as illustrated in FIG. 1A. The user 104can request that the first computing device 106 play the movie until theuser 104 falls asleep by providing a spoken utterance 108 requestingthat the movie be played until the user 104 falls asleep. For instance,the user 104 can provide a spoken utterance 108, such as, “Assistant,play a movie until I fall asleep,” to a second computing device 110,which can be, for example, a standalone-speaker device or otherassistant-enabled device. In response, an automated assistant canprocess the spoken utterance 108 and cause the first computing device106 to play the movie accordingly.

The automated assistant can access data for determining a particularcondition of the user 104. Permission to access such data can beprovided by the user 104 and subsequently inferred from the spokenutterance 108 in which the user 104 requested playback of the movieuntil the user 104 falls asleep. The data can be provided from one ormore sources such as the first computing device 106, the secondcomputing device 110, a third computing device 112 (e.g., a laptop orother portable computing device), one or more server devices, and/or anyapparatus or application capable of providing data. For instance, thedata can be at least in part generated based on an output of a lightingdevice 114, which can be connected to the first computing device 106over a local area network, such as a Wi-Fi network. The lighting device114 can include one or more sensors, such as a motion sensor, and thedata can therefore be based on an output of the motion sensor. When theautomated assistant receives the spoken utterance 108 from the user 104,the automated assistant can access the data and determine that the user104 has transitioned from a first condition to a second condition, atleast based on the data indicating a decrease in an amount of movementof the user 104.

In response to determining that the user 104 has transitioned from thefirst condition to the second condition, the first computing device 106can cause one or more changes to one or more characteristics of anoutput being provided by the first computing device 106. For instance, acharacteristic that can be changed in response to determining that theuser 104 transitioned from the first condition to the second conditioncan include audio volume, brightness of light, temperature of light,number of active speakers, equalization of sound, frequency of lightand/or sound, and/or any other characteristic of an output of acomputing device.

In some implementations, the automated assistant and/or the firstcomputing device 106 can access additional data for determining whetherthe user 104 has transitioned from the second condition to the sleepstate. The additional data can be generated based on an output from oneor more different devices, such as a wearable device 116 being worn bythe user 104 and/or the lighting device 114. For example, the wearabledevice 116 can be a watch that includes one or more sensors that areresponsive to changes in physiological features of the user 104. Thesensors of the wearable device 116 can include a heart rate sensor,blood pressure sensor, blood-oxygen sensor, respiratory rate sensor,temperature sensor, motion sensor, tactile sensor, and/or any othersensor capable of being responsive to a particular condition and/oraction of the user 104. When the user 104 is determined to be in thesleep state, at least based on processing the additional data, the firstcomputing device 106 can cause one or more changes to one or morecharacteristics of the output being provided by the first computingdevice 106. For instance, a characteristic that can be modified inresponse to determining that the user 104 entered the sleep state can bevolume, brightness, frequency, temperature of light, frequency,equalization, and/or any other characteristic discussed herein.

In some implementations, one or more characteristics of the output ofthe first computing device 106 can be changed and, additionally, theoutput can be modified according to a sleep state protocol. For example,when the automated assistant and/or the first computing device 106determines that the user 104 has entered the sleep state, the firstcomputing device 106 can be caused to modify the output according to asleep state protocol. The sleep state protocol can be directed atcontrolling the output to encourage the user 104 to stay in the sleepstate and, therefore, minimize abrupt changes in output and/or otherwisereduce a probability that the user will regress from the sleep state tothe second condition and/or the first condition. For instance, theautomated assistant and/or the first computing device 106 candetermined, based on the additional data, that the user 104 may remainin the sleep state as long as some amount of ambient noise is beingprovided by the first computing device 106 and/or the second computingdevice 110. This determination can be based on historical responsivenessof the user 104 to the ambient noise, as detected by the automatedassistant. Therefore, when the user 104 enters the sleep state, orduring a time subsequent to the user 104 entering the sleep state, theautomated assistant can cause the first computing device 106 and/or thesecond computing device 110 stop playing the output (e.g., the movie)and provide a different output, such as ambient noise. In this way, oneor more devices can be responsive to the user transitioning betweensleep states.

FIG. 2A and FIG. 2B illustrate perspective view 200 and perspective view202, respectively, of one or more timestamps being generated accordingto a condition of a user 204, when the user 204 is listening to, orotherwise perceiving, an output of a computing device. For instance, theuser 204 can request that either a first computing device 206 and/or asecond computing device 210 provide a particular output (e.g., audioand/or video output) by speaking a spoken utterance 208 such as,“Assistant, play an audiobook until I fall asleep.” In response to anautomated assistant, accessible via the second computing device 210,receiving the spoken utterance 208, the automated assistant can causethe second computing device 210 to provide an output. The output can be,for example, audio corresponding to an audiobook having a finite lengthof time, which can be symbolized by an element 222, which alsocharacterizes a temporal position 224 within the length of time that theuser 204. The temporal position 224 can identify a portion of an audiofile that the user 204 is currently perceiving. For example, if the user204 has listened to a quarter of an audiobook that is characterized byan audio file having a length of an hour, the next time the user 204initializes the audiobook for listening, the audiobook can begin at thetemporal position 224 corresponding to 15 minutes from the beginningaudio file.

Initially, when the user 204 provides the spoken utterance 208, theautomated assistant can receive the spoken utterance 208 and, inresponse and with previously granted permission from the user 204,determine a condition of the user. The condition of the user 204 cancharacterize, or be based on, one or more physiological features of theuser 204. For instance, a third computing device 212 can indicate anamount of interaction that has been occurring between the user 204 andthe third computing device 212. Additionally, or alternatively, thethird computing device 212 and/or any other source of data cancharacterize a schedule of the user 204, thereby providing informationfrom which to predict when the user 204 may desire to fall asleep, or atleast be exhibiting a restful state.

Initially, the user 204 can be determined to be in a first condition218, based on data from one or more sources. The user 204 can bedetermined to be in the first condition 218 by the automated assistant,which can cause data from one or more sources to be processed fordetermining whether the data satisfies one or more conditions foridentifying whether the user 204 is in the first condition 218 and/or isotherwise exhibiting physiological attributes corresponding to the firstcondition 218. In some implementations, the user 204 can be determinedto be in the first condition based on the user 204 at least requestingthat the automated assistant provide some amount of media playback(e.g., an audiobook or other media) that has a playback length of time(e.g., corresponding to element 222) estimated to extend into a timeperiod (e.g., 11 PM to 6:30 AM) when the user 204 is asleep. Initially,playback can begin at a temporal position 224, which is depictedgraphically in FIG. 2A.

Eventually, the user 204 can continue comprehending and/or perceivingthe media while the user 204 simultaneously transitions into a secondcondition 220. When the user 204 is determined to have transitioned fromthe first condition to the second condition, the automated assistantand/or the first computing device 206 can cause a time stamp 226 to begenerated. The time stamp can identify a temporal location within alength of time of the media (e.g., audiobook, music, movie, and/or otherfile being played back by the first computing device 206 and/or secondcomputing device 210) corresponding to a time at which the user 204transitioned from the first condition to the second condition. In otherwords, as the user 204 is perceiving an output from the first computingdevice 206 and/or the second computing device 210, the user 204 cantransition to the second condition at a point in time of playback of theoutput, and the time stamp 226 can characterize that point in time. Inthis way, the user 204 can quickly navigate to that point, within themedia data (e.g., a file, stream, and/or other source of data),corresponding to a time that the user 204 transitioned into the secondcondition. This can preserve computational resources, as the user 204would spend less time previewing different portions of the file, therebycausing less previews to be cached in memory.

In some implementations, when the user 204 is determined to havetransitioned from the first condition 218 to the second condition 220,and/or the second condition 220 to a desired condition in which the user204 is exhibiting one or more particular physiological attributes, theoutput being provided to the user 204 can be caused to change. Forinstance, when the user 204 is determined to have transitioned to thesecond condition, or another desired condition or state (e.g., a sleepstate), the media playback can transition from being based on a firstsource of data (e.g., a file or stream of an audiobook) to a secondsource of data (e.g., a file or stream of ambient sound). In this way,disruptions to a condition and/or state of the user 204 can beeliminated by mitigating disruptive endings to particular outputs.

Additionally, or alternatively, when the output provided by the firstcomputing device 206 is a visual output and the user 204 is in the firstcondition 218, the visual output can be modified in response todetermining that the user 204 is in the second condition 220. Forinstance, as illustrated in FIG. 2A and FIG. 2B, when the usertransitions from the first condition 218 to the second condition 220,the first computing device 206 can alter a level of brightness of thefirst computing device 206 in response. Alternatively, or additionally,when the user is determined to have transitioned from the firstcondition to the second condition, a visual output of the firstcomputing device 206 can be modified by adjusting one or morecharacteristics including, but not limited to, brightness, color, colortemperature, refresh rate, display size, bitrate, frame rate, gamma,bits per second, and/or any other characteristic of a computer-generatedvisual output. Changes to such characteristics as the user transitionsbetween conditions can be learned over time and adapted, in order topromote the user falling asleep without interruption and/or otherwiseexhibit one or more attributes (e.g., physical attributes associatedwith relaxation).

FIG. 3A and FIG. 3B illustrate view 300 and 302, respectively, ofimplementations wherein one or more outputs of one or more computingdevices can be modified in response to a user 304 regressing from asleep state or other desired physiological state, to a different state.For instance, the user 304 can be determined to be in a sleep state orsecond condition 318, in furtherance of staying asleep or otherwisestaying in that particular physiological state, such as a relaxed state.While the user is in the second condition, a first computing device 306can be off or otherwise providing a limited output compared to if theuser was awake. Alternatively, or additionally, a second computingdevice 310 can be playing back ambient noise in order to encourage theuser 304 staying in the second condition 318 or sleep state.Furthermore, a lighting device 314 can be located within theenvironment, such as a living room, of the user 304, but can be in anoff state when the user is in the second condition 318. Thisconfiguration of devices, settings, and/or characteristics, can becontrolled by the automated assistant and selected based on thecondition of the user 304, and with permission from the user 304.

When the automated assistant, and/or another application or device,determines that the user has transitioned from the second condition tothe first condition 320, configurations of one or more devices can bemodified in response. For instance, in response to the user 304transitioning from the second condition 318 to the first condition 320,the automated assistant can cause the lighting device 314 to emit lightaccording to one or more characteristics. Specifically, thecharacteristics can be selected according to the condition of the user.For instance, based on the user transitioning from the second conditionto the first condition, the automated assistant can cause a particularcolor and/or color temperature of light to be emitted by the lightingdevice 314. As an example, the lighting device 314 can provide a redcolor of light and a brightness level that is 5% of a maximum brightnesslevel that is capable of being emitted by the lighting device 314. Inthis way, the automated assistant can adapt the one or morecharacteristics according to a current condition of user and/or aprevious condition of the user.

Alternatively, or additionally, circumstantial data can be used incombination with a determined condition of the user 304 to identify theone or more characteristics for modifying outputs of devices within theenvironment. For example, a time of day and/or an amount of time thatthe user has been in the second condition 318 can be used to determinewhether to cause the lighting device 314 to emit red light or bluelight. Specifically, the automated assistant can cause the lightingdevice 314 to emit red light when the user 304 has been in the secondcondition for less than a threshold period of time and/or a current timeof day is within a night-time range (e.g., 10 p.m. to 4 a.m.). However,the automated assistant can also cause the lighting device 314 to emitblue light when the user has been in a second condition for equal to, orgreater than, a threshold period of time and/or a current time of day iswithin a morning or day time range (e.g., 4 a.m. to 10 p.m.). In thisway, each output can be adapted to encourage the user to stay asleep insome conditions, and/or motivate the user to stay awake in otherconditions, according to a preference of the user 304.

In some implementations, adapting characteristics when the userregresses from the second condition to the first condition 320 can beperformed for outputs of the first computing device 306, the secondcomputing device 310, and/or the third computing device 312. Forinstance, in response to the user 304 regressing from the secondcondition 318 to the first condition 320, the first computing device 306can provide a brighter light output. Alternatively, or additionally, inresponse to the user regressing from the second condition 318 to thefirst condition 320, the second computing device can provide a higheramplitude audio output relative to the audio output being provided whenthe user was in the second condition 318. Furthermore, an automatedassistant accessible via the third computing device 312 can provideambient noise when invoked by the user 304 when the user is within thesecond condition 318. Additionally, the automated assistant accessiblevia the third computing device 312 can provide light and/or a naturallanguage output when invoked by the user 304 when the user 304 is withinthe first condition 320.

FIG. 4 illustrates a system 400 for modifying one or morecharacteristics of an output of a computing device and/or automatedassistant 404 according to a condition of a user, for example, in orderto assist the user with falling asleep. The automated assistant 404 canoperate as part of an assistant application that is provided at one ormore computing devices, such as a computing device 418 and/or a serverdevice 402. A user can interact with the automated assistant 404 via anassistant interface, which can be a microphone, a camera, a touch screendisplay, a user interface, and/or any other apparatus capable ofproviding an interface between a user and an application. For instance,a user can initialize the automated assistant 404 by providing a verbal,textual, or a graphical input to the assistant interface to cause theautomated assistant 404 to perform a function (e.g., provide data,control a peripheral device, access an agent, generate an input and/oran output, etc.). The computing device 418 can include a display device,which can be a display panel that includes a touch interface forreceiving touch inputs and/or gestures for allowing a user to controlapplications of the computing device 418 via the touch interface. Insome implementations, computing device 418 can lack a display device,thereby providing an audible user interface output, without providing agraphical user interface output. Furthermore, the computing device 418can provide a user interface, such as a microphone, for receiving spokennatural language inputs from a user. In some implementations, thecomputing device 418 can include a touch interface and can be void of acamera, but can optionally include one or more other sensors.

The computing device 418 and/or other computing devices 434 can be incommunication with the server device 402 over a network 440, such as theinternet. Additionally, the computing device 418 and the other computingdevices 434 can be in communication with each other over a local areanetwork (LAN), such as a WiFi network. The computing device 418 canoffload computational tasks to the server device 402 in order toconserve computational resources at the computing device 418. Forinstance, the server device 402 can host the automated assistant 404,and computing device 418 can transmit inputs received at one or moreassistant interfaces 420 to the server device 402. However, in someimplementations, the automated assistant 404 can be hosted at thecomputing device 418 as a client automated assistant 418.

In various implementations, all or less than all aspects of theautomated assistant 404 can be implemented on the computing device 418.In some of those implementations, aspects of the automated assistant 404are implemented via the client automated assistant 422 of the computingdevice 418 and interface with the server device 402 that implementsother aspects of the automated assistant 404. The server device 402 canoptionally serve a plurality of users and their associated assistantapplications via multiple threads. In implementations where all or lessthan all aspects of the automated assistant 404 are implemented via aclient automated assistant 422 at the computing device 418, the clientautomated assistant 422 can be an application that is separate from anoperating system of the computing device 418 (e.g., installed “on top”of the operating system)—or can alternatively be implemented directly bythe operating system of the computing device 418 (e.g., considered anapplication of, but integral with, the operating system).

In some implementations, the automated assistant 404 and/or the clientautomated assistant 422 can include an input processing engine 406,which can employ multiple different modules for processing inputs and/oroutputs for the computing device 418 and/or the server device 402. Forinstance, the input processing engine 406 can include a speechprocessing module 408 that can process audio data received at anassistant interface 420 to identify the text embodied in the audio data.The audio data can be transmitted from, for example, the computingdevice 418 to the server device 402 in order to preserve computationalresources at the computing device 418.

The process for converting the audio data to text can include a speechrecognition algorithm, which can employ neural networks, word2vecalgorithms, and/or statistical models for identifying groups of audiodata corresponding to words or phrases. The text converted from theaudio data can parsed by a data parsing module 410 and made available tothe automated assistant as textual data that can be used to generateand/or identify command phrases from the user. In some implementations,output data provided by the data parsing module 410 can be provided to aparameter module 412 to determine whether the user provided an inputthat corresponds to a particular action and/or routine capable of beingperformed by the automated assistant 404 and/or an application or agentthat is capable of being accessed by the automated assistant 404. Forexample, assistant data 416 can be stored at the server device 402and/or the computing device 418, as client data 432, and can includedata that defines one or more actions capable of being performed by theautomated assistant 404 and/or client automated assistant 422, as wellas parameters necessary to perform the actions.

In some implementations, the other computing device 434 can receiveinputs from the computing device 418 and/or the server device 402, andprovide outputs for the user, and/or transmit outputs to the computingdevice 418 and/or the server device 402. For instance, the user canprovide a request for the client automated assistant 422 to provide anoutput for assisting the user with falling asleep. The request can beembodied as a spoken utterance such as, “Assistant, play my televisionseries until I fall asleep.” In response, audio data corresponding tothe spoken utterance can be provided to the server device 402 andprocessed by the input processing engine 406. The input processingengine 406 can identify the television series that the user is referringto, and cause the computing device 418 and/or another computing device434 to provide an audio-visual output corresponding to the televisionseries.

Furthermore, and in some implementations, the computing device 418and/or the server device 402 can include a condition engine 424. Thecondition engine 424 can determine and/or characterize a circumstance inwhich an automated assistant received a request. The circumstance can becharacterized based on one or more sources of data, such as data fromthe computing device 418, data from the server device 402, and/or datafrom one or more other computing devices 434. In some implementations,the other computing devices 434 can include a wearable device, aportable computing device, a vehicle, a robotic device, and/or any othercomputing device capable of providing data to another computing device.One or more other computing devices 434 can include one or more inputdevices 436 and/or one or more output devices 438. For instance, the oneor more input devices 436 can include one or more sensors, interfaces,processors, memory devices, receivers, and/or any other apparatuscapable of receiving an input. Furthermore, the one or more outputdevices 438 can include one or more interfaces such as a speaker, adisplay panel, a light, a motor, and/or any other apparatus that canreceive a signal from a computing device.

When the other computing devices 434 include a wearable device, thecondition engine 424 can determine the condition of the user and/or therequest provided by the user based on data generated based on one ormore input devices for 436 of the wearable device. For example, thewearable device can include one or more sensors capable of beingresponsive to changes in physiological attributes of the user. Datacharacterizing the physiological attributes of the user can betransmitted from the other computing device 434 to the condition engine424 in order to determine a condition of the user. The condition engine424 can determine, for example, that the user is in a first condition,and has therefore initialized actions in furtherance of falling asleep.The determination of the condition can then be communicated by thecondition engine 424 to the characteristic engine 426.

The characteristic engine 426 can identify one or more characteristicsof one or more outputs to adapt according to the condition determined bythe condition engine 424 and/or the request or action to be performedfor the user. For instance, when the user is determined to haverequested a television series to be output, the characteristic engine426 can determine based on the condition, and/or the request, one ormore characteristics of the output to modify. In some implementations, acharacteristic of an audio portion of the output can be modified, andanother characteristic of a visual portion of the output can be modifiedaccording to the condition of the user. Specifically, as an example, avolume of the audio portion of the output can be adjusted to be lowerrelative to a previous volume of the audio portion of the output whenthe user previously requested the output be provided. Furthermore, as anexample, a color temperature of the visual portion of the output can bewarmer, or include less blue light, relative to a previous colortemperature of the visual portion of the output when the user previouslyrequested the output be provided.

Additional data can be transmitted to the condition engine 424 fordetermining whether the user has transitioned out of the firstcondition. For instance, the server device 402, the other computingdevice 434, and/or the computing device 418 can generate data from whichthe condition engine 424 can determine the condition of the user. Insome implementations, when the user is determined to have transitionedfrom the first condition to a second condition, a timestamp engine 430can identify a temporal location within an output of the computingdevice 418, or another computing device 434, in which to direct orassign a particular time stamp. Furthermore, in some implementations,when the user is determined to have transitioned from the secondcondition to a sleep state, or has otherwise been determined to havefallen asleep, the timestamp engine 430 can identify another temporallocation within the output of the computing device 418 at which todirect or assign another particular time stamp. In this way, should theuser fall asleep during playback of a media source, the user can easilyidentify a location where they may have fallen asleep or otherwise beeninattentive to the media. In some implementations, the timestamp engine430 can generate a timestamp based on a predicted time at which the userwill transition between conditions and/or physiological states. Such apredicted time can be based on historical data (e.g., stored as clientdata 424 and/or assistant data 416) that characterizes times at whichthe user typically transitions between conditions, such as when the userfalls asleep.

In some implementations, the automated assistant 404, and/or the clientautomated assistant 422 can respond to spoken utterances, such as aninvocation phrase, from the user based on a determined condition of theuser. For example, when the condition engine 424 determines that theuser is in a second condition, the client automated assistant 422 canoperate according to a setting wherein an assistant interface 420, suchas a speaker, will output ambient noise in response to an invocationphrase such as, “Assistant . . . ” Furthermore, one or morecharacteristics of the responsive output from the automated assistantcan be based on the condition, the user, and/or any other informationthat can provide a basis for modifying an output of a device. Forinstance, the automated assistant can determine that user provided theinvocation phrase, identify a particular ambient noise selected by, orassigned to, the user, and cause the particular ambient noise to beoutput by the computing device 418. Should a different user provide theinvocation phrase, the automated assistant can identify the differentuser, identify a different ambient noise selected by, or assigned to,the different user, and cause the different ambient noise to be outputby the computing device 418. Additionally, or alternatively,characteristics of the responsive output can be adjusted according tothe condition, the user, and/or any other information.

For instance, when the responsive output is a light output, a propertyof light, such as temperature and/or brightness, can be selectedaccording to the condition, the user, and/or any other information. Forexample, when the first user provides an invocation price, a firstpattern of light can be emitted in response, and when a second userprovides the invocation phrase, a second pattern of light, which isdifferent than the first pattern of light, can be emitted in response.The responsive output can be an indication that the automated assistanthas acknowledged the invocation phrase and/or is awaiting furtherinstructions from the user. By providing a responsive output that is nota natural language output, such as, “How can I help you?” the user willbe less disturbed by the output, should the user be attempting to fallasleep when the user provided the invocation phrase. Furthermore, suchresponsive output can mitigate the chance of the automated assistantwaking up other users within the environment or home in which the userprovided the invocation phrase.

In some implementations, the system 400 can be responsive to a userregressing away from a sleep state, or otherwise transitioning out of aparticular condition. For instance, when the user awakens from a sleepstate, the automated assistant can determine a condition of the userwhen the user awakens and/or immediately before the user wakes up.Depending on what the user is attempting to do when they wake up, theautomated assistant and/or one or more other computing devices 434 canrespond accordingly. For instance, when the condition engine 424determines based on additional data that the user has been in a sleepstate for less than a threshold period of time and has awakened, thecondition engine 424 can communicate the condition to the characteristicengine 426. The characteristic engine 426 can modify an output ofanother computing device 434 to provide a light output, such as a redlight output, in order to illuminate a path for the user while alsoproviding less stimulating light for preventing further awakening theuser. Alternatively, when the condition engine 424 determines, based onadditional data, that the user has been in a sleep state for at least athreshold period of time and woken up, the condition engine 424 cancommunicate this condition to the characteristic engine 426. Thecharacteristic engine can then modify an output of another computingdevice 434 to provide a light output, such as a blue light output, inorder to illuminate a path for the user and also provide some amount ofstimuli that would assist the user in waking up. In someimplementations, the threshold period of can be dynamic and/or adjustedaccording to sleep habits of the user and/or preferences of the userlearned over time by the automated assistant.

FIG. 5 illustrates a method 500 for identifying timestamps correspondingto a temporal location within of an output that a user transitionedbetween conditions and/or fell asleep. The method 500 can be performedby one or more computing devices, applications, and/or any otherapparatus or module capable of interacting with a computing device thatis accessing a file. The method 500 can include an optional operation502 of receiving a request for an automated assistant to cause acomputing device to playback an output while a user is acting infurtherance of falling asleep. The output can correspond to a file,stream, and/or any other source of data that a computing device canprocess in order to provide an output that can perceived by the user.The output can, for example, correspond to a podcast that is stored at aserver device, which is in communication with a client device via whichthe user accesses the automated assistant. The client device can be acomputing device that includes an automated assistant interface, such asa microphone, and the user can cause the podcast to be output by theclient device by providing a spoken utterance such as, “Assistant, playmy podcast.”

The method 500 can further include an operation 504 of causing thecomputing device to provide the output in furtherance of the playbackreaching a final point in a length of playback time for the data uponwhich the output is based. For instance, the podcast can have a lengthof playback, such as 1 hour, and the automated assistant can initiallycause the podcast to begin at a first timestamp 0:00. The user canprovide the spoken utterance for initializing playback of the podcastwhen the user has initially lied down on their couch, in furtherance oftaking a nap. Furthermore, although the user has provided the spokenutterance to the client device, the output can be provided from theclient device and/or a separate client device that is capable ofproviding an output that the user can comprehend when the user is ontheir couch. For instance, the user can provide the spoken utterance totheir standalone speaker-display device, and the output can beinitialized at their television, at least based on their televisionbeing connected to an audio system capable of more readily providing theoutput to the user.

The method 500 can further include an operation 506 of processing datathat characterizes a condition of the user when the user is located inan environment in which an output is provided according to the playbackof the file. The data can be provided by one or more different computingdevices, such as one or more client devices located within theenvironment and/or connected to a network available in the environment,and/or one or more server devices, such as a server device that hosts atleast a portion of the automated assistant and/or other data. Forinstance, the data can be provided by a wearable device that the user iswearing when the user initially causes playback of the podcast to occur.The data provided by the wearable device can include physiological data,which can be processed to at least assist in determining the conditionof the user. Additionally, or alternatively, the data can be provided bya client device that is located within the environment with the user,and can therefore detect various environmental characteristics of theenvironment, and/or any particular characteristics exhibited by theuser. For instance, the client device can include a microphoneconfigured to be responsive to noises made by the user, devices,inanimate objects, and/or any other feature of the environment. The datafrom the client device can provide an indication of how active the usercurrently is, and therefore be used to determine a condition or state ofthe user.

The method 500 can further include an operation 508 of determining acondition of the user. The condition of the user can be based on thedata collected from one or more different sources. Additionally, oralternatively, the data can characterize a frequency of motion of theuser, a physiological condition of the user, and/or any other feature ofa user that can indicate a state of the user. When the user isdetermined to be in a first condition, the method 500 can proceed tooperation 510 of generating a first time stamp corresponding to aposition within the playback of the output (e.g., the podcast). In orderto determine that the user is in the first condition, the data can beprocessed to determine whether the user is stationary and/or has beenstationary for a threshold period of time (e.g., when the user hasinitially lied down on their couch). The threshold period of time can bepre-determined or learned, by the client device, over time in order tomore accurately determine when the user is in the first condition.Additionally, or alternatively, in order to determine that the user isin the first condition, the data can be processed to determine that aphysiological attribute of the user indicates that the user isexhibiting an initial condition of relaxation relative to their previouscondition. For instance, the data can be provided by a wearable devicethat provides at least some amount of data corresponding to one or morephysiological attributes of the user, such as heartrate, respiratoryrate, blood pressure, blood-oxygen level, frequency of motion, and/orany other physiological attribute. When one or more physiologicalattributes satisfy one or more respective conditions (e.g., heart rateand/or respiratory rate satisfy particular thresholds), the user can beconsidered to be in a first condition.

In response to determining that the user is in the first condition, afirst time stamp can be generated. The first time stamp can correspondto a position within playback of the output being provided by the clientdevice. For instance, if the podcast initially began at time stamp 0:00,and 15 minutes later the user was determined to be in the firstcondition, the first time stamp can be 15:00. In this way, although theuser may not be asleep within the first condition, the user entering thefirst condition can nonetheless be an indication that the user may bepaying more or less attention to the podcast or other output, relativeto just before the user entered the first condition. The method 500 canreturn to operation 506 where additional data continues to be processedto determine whether the user is still in the first condition or hastransitioned between conditions and/or other states.

When the user is determined to have transitioned to the secondcondition, the method 500 can proceed to operation 512 of generating asecond time stamp corresponding to another position within playback ofthe output. The data can indicate that the user has transitioned to thesecond condition when one or more conditions are satisfied by the data.For instance, the data can characterize one or more physiologicalattributes, as discussed herein, and when one or more physiologicalattributes satisfy one or more conditions. In some implementations, whena particular physical attribute goes beyond a threshold associated withthe first condition, the user can be considered to be in the secondcondition. For instance, when a heartrate of the user falls below athreshold corresponding to the first condition, the user can beconsidered to be in a second condition. Additionally, or alternatively,when a respiratory rate falls within a learned and/or dynamic thresholdcorresponding to the second condition, the user can be considered to bewithin the second condition. It should be noted that any number ofconditions can be defined per user. For instance, depending on one ormore different medical conditions of the user, a user may have multipleconditions that they transition between, therefore, operations of theautomated assistant, the client device, and/or any other device canoperate according to such conditions.

In response to determining that the user has transitioned to the secondcondition, a second time stamp can be generated. The second time stampcan correspond to another temporal position within the playback of theoutput during which the user was determined to be in the secondcondition. For instance, when the output is a podcast that initiallystarted at the time stamp 0:00, and the user was determined to be withinthe second condition 25 minutes later, the second time stamp can be25:00. In this way, should the user subsequently fall asleep, the userwill be able to start the podcast from first time stamp or the secondtime stamp, when they wake up.

When the user is determined to have transitioned to a sleep state orotherwise determined to have fallen asleep, the method 500 can proceedto an optional operation 514 of causing playback of the output accordingto a sleep state protocol. In other words, the output can be modifiedaccording to a sleep state protocol, which can cause the output to ceaseover a period of time. For instance, the sleep state protocol can causethe output to gradually decrease as long as physiological attributesremain relatively constant as the user remains in the sleep state. Inthis way, an abrupt ending to the output can be bypassed in order toprovide a smoother transition for the environment to eventually nolonger have any artificial noise emitted by the client device.Alternatively, or additionally, playback of the output can betransitioned into, or combined with, a different output, such as ambientnoise. In other words, as the output continues while the user is asleep,a different output can gradually increase in amplitude simultaneouslywith the initial output (e.g., the podcast) gradually decreasing inamplitude. In some implementations, a slope of the increase or decreasein amplitude of the output or they different output can be based on oneor more physiological attributes of the user. For instance, historicaldata can indicate that the user is a light sleeper and/or easily awokenby changes to noise. Therefore, the slopes for the increase in thedifferent output and the decrease in the original output can be lowrelative to slopes assigned for other persons' sleep protocols, in orderto mitigate perceivable changes in sound amplitude.

When the user is determined to have transitioned from the second stateto the sleep state, and/or has otherwise been determined to be in thesleep state, the method 500 can proceed to operation 516 of causingplayback of the output to cease. In some implementations, the output cancease when the user is determined to be asleep, and in other limitationsthe output can be modified such that a file or a stream, from which theoutput is based, can be switched to a different file or a differentstream. In some implementations, although the output has ceased,additional data can be continually analyzed or processed according tothe operation 506. In this way, should the user awake and exhibitcharacteristics associated with the first condition or the secondcondition, another output can be initialized in response. For example,although the user was listening to a podcast just before the output ofthe podcast with ceased, should the user awaken after the podcast hasceased, a different output, such as ambient noise, can be the subject ofplayback that is based on a different file or a different stream. Onemore characteristics of the different output can be selected accordingto whether the user is within the first condition, the second condition,or is asleep, as discussed herein.

FIG. 6 illustrates a method 600 for modifying an output of a computingdevice according to a condition of a user. The method 600 can beperformed by one or more computing devices, applications, and/or anyother apparatus or module capable of modifying an output of a computingdevice. The method 600 can optionally include an operation 602 ofreceiving a request for an automated assistant to cause a computingdevice to provide an output into an environment according to a conditionof a user. Specifically, the user can provide the spoken utterance to aclient device that includes an automated assistant interface, and thespoken utterance can be, “Assistant, play ambient noise until I fallasleep.” The spoken utterance can be received at the automated assistantinterface, converted into audio data, and transmitted to a separateserver device for processing. The server device can then respond with anaction for the client device to perform, and accordingly initializeplayback of the ambient noise.

In some implementations, depending on the condition of the user, theautomated assistant can optionally indicate that automated assistantheard the spoken utterance from the user by causing playback of ambientnoise, and/or any other output from a modality that is different from anoutput or modality that the automated assistant would otherwise use toacknowledge receipt of a spoken utterance. For example, when the userprovides a spoken utterance after entering their bedroom past aparticular time, the client device that receives the spoken utterancecan cause playback of an ambient noise, such as rainforest sounds. Inthis way, should another person be in the room sleeping already, theother person would not be disturbed by the automated assistantresponding with a loud, natural language output, such as “Ok,” or anyother acknowledgement of receipt of a spoken utterance. Rather, inresponse to a spoken utterance, an output that is less abrupt can beoutput from the client device in order to indicate to the user that thespoken utterance was received by the automated assistant.

In some implementations, the output provided in response to a spokenutterance from a particular user can change from user to user. Forexample, a first user can provide a spoken utterance when entering theirbedroom at night, and a client device within their bedroom can outputrainforest noises in order to indicate that the automated assistant hasacknowledged receipt of the spoken utterance. Furthermore, a second usercan provide the spoken utterance when entering the bedroom at night, andthe client device within their bedroom can output classical music.Preferences for responsive sounds and/or other outputs can be learnedover time as the user interacts with the automated assistant and/or anycombination thereof. In some implementations, a first user may preferthat the automated assistant confirm acknowledgement by responding withambient noise, while a second user may prefer that the automatedassistant confirm that acknowledgement by emitting one or more patternsof light. Certain preferences for outputs can be based on the user thatis speaking, a condition of the user, one or more conditions of one ormore other users, and/or any other data from which a preference can bebased upon.

The method 600 can further include an optional operation 604 of causingthe computing device to provide the output into the environment infurtherance of causing the user to fall asleep. The client device to canbegin emitting ambient noise while the user is acting in furtherance offalling asleep. The ambient noise can have one or more characteristics,which can be modified according to one more computing devices that are,for example, tasked with ensuring that the ambient noise is encouragingthe user to fall asleep, instead of regressing away from falling asleep.Initially, the one or more characteristics of the output can be based ona default preference, a preference previously set by the user, and/or adetected condition at the time the output started, or just before theoutput started. For instance, if the user provided the spoken utteranceas a whisper to the automated assistant, the automated assistant cancapture the amplitude of the whisper as part of the condition in whichthe user provided the spoken utterance. The output can then be at leastpartially based on the condition, and, specifically, can be based on anamplitude of the spoken utterance provided to the automated assistant.

The method 600 can further include an operation 606 of processing datathat characterizes a condition of the user when the user is located inan environment in which the output is being provided by the computingdevice. As discussed herein, data that characterizes a condition of theuser can be provided from one or more different applications, devices,and/or any other apparatus or module capable of providing data. In someimplementations, data used to determine a condition can include temporaldata corresponding to a time of day, motion data corresponding to anamount of motion within one or more environments, audio datacorresponding to the spoken utterance and/or any other noises associatedwith the user and/or the environment, schedule data based on a storedcalendar or schedule(s) of one or more users, physiological datacorresponding to one or more physiological attributes of one or moreusers, and/or any other information from which a condition of a user canbe determined.

The method 600 can further include an operation 608 of determining acondition of the user. As discussed herein, the condition of the usercan be based on data collected from one or more different sources. Whenthe data indicates that the user is in a first condition, the method 600can proceed to an operation 610 of causing the computing device toprovide the output such that the output has a first characteristic. Whenthe user is in the first condition, the data can indicate that the useris in a more relaxed state than a previous state or another state theyhave otherwise been in for a majority of a day. For instance, a user canbe considered to be in the first condition when their heartrate was anaverage of 70 beats per minute (bpm) for a majority of the day, andtheir wearable device currently indicates their heartrate is 65 bpm(e.g., less than 95% of the bpm for the majority of the day, or anyother percentage threshold). In some implementations, the user can beconsidered to be in a first condition in response to the user providinga request to the automated assistant indicating that the user will beattempting to fall asleep or otherwise relax. For instance, in responseto the automated assistant receiving the spoken utterance, “Assistant,play ambient noise until I fall asleep,” the automated assistant candetermine that the user is intending to fall asleep based on the contentof the spoken utterance (e.g., “ . . . until I fall asleep.”). In someimplementations, for purposes of identifying one or more characteristicsto select for modifying the output (e.g., the ambient noise), theautomated assistant can consider the user in the first condition untiladditional data indicates otherwise.

When the user is determined to be in the first condition and the outputof the computing device is caused to have a first characteristicaccording to operation 610, the method 600 can return to operation 608,in which additional data can be processed. The additional data can beprocessed to determine whether the user is still in the first conditionor has transitioned out of the first condition (e.g., to a differentcondition and/or has fallen asleep). When the user is determined to havetransitioned from the first condition to the second condition, and/orotherwise has entered the second condition, the method 600 can proceedto operation 612 of causing the computing device to provide the outputsuch that the output has a second characteristic.

In some implementations, the second characteristic can correspond to anamplitude of the output that is different from a previous amplitudecorresponding to the first characteristic. For example, the output canbe an audio output and the first characteristic can be an amplitude thatis greater than an amplitude assigned for the second characteristic. Inother words, when the user is determined to have transitioned from thefirst condition to the second condition, the audio output will decreasein amplitude. In some implementations, the first characteristic and thesecond characteristic can be associated with an equalization of an audiooutput. Therefore, in response to the user transitioning from the firstcondition to the second condition, amplitudes of one or more ranges offrequencies can be different according to how the first characteristicand the second characteristic are respectively defined. For example, thefirst characteristic can have a flat equalization, such that no changeis made to the equalization of an initial source of the output, and thesecond characteristic can operate as a high pass, low pass, and/or bandpass filter, thereby limiting an amplitude of particular branches offrequencies of the output. As a result, when the user transitions fromthe first condition to the second condition, higher frequency sounds,lower frequency sounds, and/or middle frequency sounds, and/or acombination thereof, will be adjusted in order to mitigate disruptionsto the user eventually reaching a sleep state or otherwise fallingasleep.

In some implementations, when the output is a visual and/or audiooutput, the first characteristic and the second characteristic cancorrespond to properties of light being admitted as part of the output.For instance, if the user has requested that the automated assistantplay a movie until the user falls asleep, a brightness of the displaypanel that is outputting the movie can be adjusted in response to theuser transitioning from the first condition to the second condition.Alternatively, or additionally, an equalization of the frequencies oflight being emitted by the display panel can be adjusted in response tothe user transitioning from the first condition to the second condition.For instance, when the user is determined to have transitioned from thefirst condition to the second condition, an amount of blue lightapparent in the output from the display panel can be decreased inresponse. In some implementations, one or more properties of light canbe adjusted in response to determining that the user has transitionedbetween different conditions, has fallen asleep, and/or has woken up.

When the user is determined to have transitioned from the second stateto the sleep state, or has otherwise fallen asleep, the method 600 canproceed to an optional operation 614 of causing the computing device toprovide the output according to a sleep protocol. The operation 614 canbe the same as the operation 514 discussed with respect the method 500,and/or can be executed and/or modified according to any detailsdiscussed herein. For instance, in some implementations, when the outputis a visual and/or audio-visual output, an amplitude or brightness ofthe light can be gradually decreased as the user remains asleep. Thebrightness can be decreased until eventually, at operation 616, thecomputing device can be caused to cease providing the output. In someimplementations, one or more characteristics of light and one or morecharacteristics of audio can be adjusted concurrently while the userremains asleep in order to mitigate interruptions of the sleep of theuser via abrupt changes in the environment. In some implementations, oneor more characteristics of the light and/or the audio can be adjustedaccording to you changes in the data as the user remains asleep, and/orphysiological attributes of the user as the user remains asleep. Forinstance, changes in one or more characteristics of the audio and/orvideo can be based on a respiratory rate of the user and, optionally,whether such a basis for the output has been previously determined toassist the user with staying asleep.

When the user is determined to have transitioned from the second stateinto the sleep state, and/or has otherwise entered the sleep state, themethod 600 can proceed to operation 616 of causing the computing deviceto cease providing the output. The output can be stopped in order toeliminate further unnecessary consumption of processing and/or networkbandwidth. Furthermore, despite the output being ceased at the computingdevice, the method 600 can proceed back to operation 606, whereinadditional data can be processed in order to determine whether the userhas transitioned out of the sleep state, or is expected to transitionout of a sleep state. For instance, if the user happens to have a dreamthat wakes them up, the additional data can characterize the suddenmotion, noise, and/or other environmental features affected by the userwaking up. The data can be processed in order to identify a condition inwhich the user has transitioned into. For example, if the user hastransitioned into the first condition, the method 600 can proceed fromoperation 608 to operation 610. The output can be reinitialized as aresult, in order to encourage the user to again progress towards a sleepstate, assuming that the user has woken up within a time period thatthey typically prefer to be asleep.

FIG. 7 is a block diagram of an example computer system 710. Computersystem 710 typically includes at least one processor 714 whichcommunicates with a number of peripheral devices via bus subsystem 712.These peripheral devices may include a storage subsystem 724, including,for example, a memory 725 and a file storage subsystem 726, userinterface output devices 720, user interface input devices 722, and anetwork interface subsystem 716. The input and output devices allow userinteraction with computer system 710. Network interface subsystem 716provides an interface to outside networks and is coupled tocorresponding interface devices in other computer systems.

User interface input devices 722 may include a keyboard, pointingdevices such as a mouse, trackball, touchpad, or graphics tablet, ascanner, a touchscreen incorporated into the display, audio inputdevices such as voice recognition systems, microphones, and/or othertypes of input devices. In general, use of the term “input device” isintended to include all possible types of devices and ways to inputinformation into computer system 710 or onto a communication network.

User interface output devices 720 may include a display subsystem, aprinter, a fax machine, or non-visual displays such as audio outputdevices. The display subsystem may include a cathode ray tube (CRT), aflat-panel device such as a liquid crystal display (LCD), a projectiondevice, or some other mechanism for creating a visible image. Thedisplay subsystem may also provide non-visual display such as via audiooutput devices. In general, use of the term “output device” is intendedto include all possible types of devices and ways to output informationfrom computer system 710 to the user or to another machine or computersystem.

Storage subsystem 724 stores programming and data constructs thatprovide the functionality of some or all of the modules describedherein. For example, the storage subsystem 724 may include the logic toperform selected aspects of method 500, method 600, and/or to implementone or more of first computing device 106, first computing device 206,first computing device 306, second computing device 110, secondcomputing device 210, second computing device 310, server device 402,computing device 418, other computing devices 434, and/or any othermodules or apparatuses discussed herein.

These software modules are generally executed by processor 714 alone orin combination with other processors. Memory 725 used in the storagesubsystem 724 can include a number of memories including a main randomaccess memory (RAM) 730 for storage of instructions and data duringprogram execution and a read only memory (ROM) 732 in which fixedinstructions are stored. A file storage subsystem 726 can providepersistent storage for program and data files, and may include a harddisk drive, a floppy disk drive along with associated removable media, aCD-ROM drive, an optical drive, or removable media cartridges. Themodules implementing the functionality of certain implementations may bestored by file storage subsystem 726 in the storage subsystem 724, or inother machines accessible by the processor(s) 714.

Bus subsystem 712 provides a mechanism for letting the variouscomponents and subsystems of computer system 710 communicate with eachother as intended. Although bus subsystem 712 is shown schematically asa single bus, alternative implementations of the bus subsystem may usemultiple busses.

Computer system 710 can be of varying types including a workstation,server, computing cluster, blade server, server farm, or any other dataprocessing system or computing device. Due to the ever-changing natureof computers and networks, the description of computer system 710depicted in FIG. 7 is intended only as a specific example for purposesof illustrating some implementations. Many other configurations ofcomputer system 710 are possible having more or fewer components thanthe computer system depicted in FIG. 7.

In some implementations, a method implemented by one or more processorsis set forth as including operations such as causing a first output tobe emitted by a computing device into an environment when a user islocated within the environment, wherein the computing device isconfigured to adjust at least one characteristic of provided outputaccording to one or more physiological attributes of the user. Themethod can further include accessing, when the first output is beingemitted by the computing device, physiological data that characterizesthe one or more physiological attributes of the user, wherein thephysiological data is generated based on a sensor output of a separatedevice that is in communication with the computing device. The methodcan further include determining, based on the physiological data, thatthe user has progressed closer to a sleep state or has progressed to thesleep state; and causing, in response to determining that the user hasprogressed closer to the sleep state or is in the sleep state, a secondoutput to be emitted by the computing device into the environment,wherein the second output is emitted with the at least onecharacteristic being adjusted in response to determining that the userhas progressed closer to the sleep state or is in the sleep state, andwherein the adjustment of the characteristic is configured to reduce aprobability that the user will regress from the sleep state.

In some implementations, the first output and the second output comprisecorresponding portions of media that has a total length of playbacktime, and the method further comprises: generating, in response todetermining that the user has progressed closer to the sleep state orhas progressed to the sleep state, a timestamp, corresponding to atemporal position within the total length of playback time, at which theuser progressed closer to the sleep state or progressed to the sleepstate during playback of the media. In some implementations, the methodcan further include receiving, subsequent to generating the timestampand halting output of the media, a request from the user to resumeplayback of media; and causing, in response to receiving the requestfrom the user, playback of the media to resume from the temporalposition corresponding to the timestamp. In some implementations, themethod can further include in response to determining that the user hasprogressed closer to the sleep state or has progressed to the sleepstate: causing playback of separate media, and causing playback of themedia to cease subsequent to determining that that the user hasprogressed closer to the sleep state or has progressed to the sleepstate. In some implementations, the first output is a first light outputand the second output is a second light output, and the method furthercomprises: determining, prior to causing the first output to be emittedby the computing device into the environment, that the user has movedacross a portion of the environment, wherein causing the first output tobe emitted by the computing device into the environment is in responseto determining that the user has moved across the portion of theenvironment. In some implementations, the first light output correspondsto a higher color temperature of light and/or a higher brightness oflight, relative to the second light output. In some implementations, theseparate device is a wearable device that is worn by the user and thatincludes one or more sensors that provided the sensor output.

In other implementations, a method implemented by one or more processorsis set forth as including operations such as receiving, from a user, aspoken utterance corresponding to a request for an automated assistantto cause media to be rendered, the media having a fixed duration with atotal length of playback time. The method can further include inresponse to receiving the spoken utterance, causing a computing device,from which the automated assistant is accessible, to render the media infurtherance of the media reaching a final point in the total length ofthe playback time. The method can further include processing data thatcharacterizes one or more physiological attributes of the user when theuser is located in an environment in which the media is being rendered.The method can further include determining, based on processing thedata, that the user has progressed closer to a sleep state or to thesleep state; and generating, in response to determining that the userhas progressed closer to the sleep state or to the sleep state, atimestamp corresponding to a temporal position, within the total lengthof playback time, at which the user progressed closer to the sleep stateor to the sleep state during playback of the media.

In some implementations, the method can further include causing thecomputing device to continue performing playback of the media subsequentto generating the timestamp and determining that the user has progressedcloser to the sleep state or to the sleep state. In someimplementations, the method can further include subsequent to generatingthe timestamp and determining that the user has progressed closer to thesleep state or to the sleep state: processing additional data thatcharacterizes the one or more physiological attributes of the user, anddetermining, based on processing the additional data, that the user hasprogressed to the sleep state or to a deeper state of sleep. In someimplementations, the method can further include generating, in responseto determining that the user has progressed to the sleep state or to thedeeper state of sleep, a separate timestamp corresponding to a separatetemporal position, within the total length of playback time, at whichthe user was determined to have progressed to the sleep state or to thedeeper state of sleep. In some implementations, the method can furtherinclude causing playback of the media to cease subsequent to determiningthat the user has progressed to the sleep state or to the deeper stateof sleep. In some implementations, the method can further includecausing, subsequent to playback of the media ceasing and/or concurrentwith the playback of the media ceasing, playback of separate media to beinitialized in response to determining that the user has progressed tothe sleep state or to the deeper state of sleep. In someimplementations, one or more characteristics of the playback of theseparate media are at least temporarily based on, or shared with, one ormore other characteristics of the playback of the media. In someimplementations, the one or more other characteristics includes a volumeof audio corresponding to the playback of the media or a level ofbrightness corresponding to a playback of the media.

In yet other implementations, a method implemented by one or moreprocessors is set forth as including operations such as processing datathat is based on one or more sensors in an environment to determine acurrent condition of a dynamic condition of a user, wherein sound isbeing emitted, in the environment, from a computing device that isconfigured to adjust an adjustable characteristic of the sound based onthe dynamic condition of the user. The method can further includedetermining, based on processing the data, whether a present value, ofthe adjustable characteristic of the sound, is unsuitable for thecurrent condition of the user, wherein determining whether the presentvalue is unsuitable for the current condition of the user comprisesdetermining whether the present value will increase a probability thatthe user will regress away from a desired condition. The method can whenthe present value is determined to be unsuitable for the currentcondition of the user: selecting an alternate value for the adjustablecharacteristic of the sound, wherein the alternate value is selected todecrease the probability of the user regressing from the desiredcondition, and causing the computing device to transition the sound fromexhibiting the present value to the alternate value.

In some implementations, the present value of the sound corresponds to avolume of the sound being emitted into the environment and the alternatevalue of the sound corresponds to a lower volume of sound, the lowervolume of sound being lower relative to the volume of the present valueof the sound. In some implementations, the method can further includedetermining whether the present value of the sound will increase theprobability that the user will regress away from the desired conditionfurther based on a correspondence between the current condition of theuser and the present value of the sound. In some implementations, theone or more sensors in the environment, on which the data is based,comprise a sensor that is integral to a wearable computing device beingworn by the user. In some implementations, the data includescircumstantial data that is based on outputs from multiple differentcomputing devices connected to a local area network with the computingdevice. In some implementations, the data further characterizes apredicted event that is associated with an interruption of the userreaching the desired condition, and the method further comprises:determining, based on processing the data, that the predicted event isexpected to occur and cause the interruption, wherein determiningwhether the present value of the sound is unsuitable for the desiredcondition of the user is further based on determining that the predictedevent is expected to occur. In some implementations, the method canfurther include determining whether the present value of the sound willincrease the probability that the user will regress away from thedesired condition further based at least on determining that thepredicted event is expected to occur, wherein the probability is basedat least on a historical responsiveness of the user to a previous soundexhibiting the present value.

In some implementations, the method can further include subsequent tocausing the computing device to transition the sound from exhibiting thepresent value to the other characteristic: determining that the user hasprovided a spoken utterance corresponding to a request for the automatedassistant to cause a particular output to be provided according to therequest, and causing the particular output to be provided based on thecurrent condition of the user. In some implementations, wherein causingthe particular output to be provided based on the current condition ofthe user includes: selecting, based on the current condition of theuser, one or more particular for the particular output, wherein the oneor more particular values are selected to decrease the probability ofthe user regressing from the current condition. In some implementations,the particular output requested by the user is an audio output and theone or more particular values correspond to characteristics that includea volume of the audio output, and/or the particular output is a visualoutput and the one or more particular values correspond tocharacteristics that include a brightness and/or color temperature ofthe visual output.

In yet other implementations, a method implemented by one or moreprocessors of an assistant computing device is set forth as includingoperations such as transitioning the assistant computing device from afirst state to a second state, wherein in the first state the assistantcomputing device does not perform certain processing of audio datadetected via one or more microphones of the assistant computing device,and wherein in the second state the assistant computing device performsthe certain processing of audio data detected via the one or moremicrophones. In some implementations, the method can further include,responsive to transitioning the assistant computing device to the secondstate, and for a duration of the second state: rendering ambient audiovia one or more speakers of the assistant computing device; andresponsive to cessation of the second state: ceasing the rendering ofthe ambient audio.

In some implementations, the method can further include, when in thefirst state, monitoring for occurrence of an invocation phrase byprocessing audio data detected via the one or more microphones usingonly a local invocation model stored locally at the assistant computingdevice; wherein transitioning the assistant computing device from thefirst state to the second state is based on detecting an occurrence ofthe invocation phrase in a portion of the audio data. In someimplementations, the method can further include selecting the ambientaudio based on the ambient audio being stored in association with a userprofile that is determined based at least in part on further analysis ofthe portion of the audio data. In some implementations, the method canfurther include determining a volume for the rendering of the ambientaudio, wherein rendering the ambient audio is at the determined volume.In some implementations, determining the volume is based on one or moreof: a level of background noise as detected via the one or moremicrophones, an estimated distance of an active user of the assistantcomputing device, or one or more physiological characteristics of theactive user. In some implementations, the certain processing comprisesone or more of: transmitting the audio data to a remote automatedassistant server, or speech-to-text processing. In some implementations,in the first state the assistant device is rendering a response that isresponsive to a previous request received via the assistant device, andwherein transitioning the assistant computing device from the firststate to the second state occurs automatically in response to completionof rendering the response.

In situations in which the systems described herein collect personalinformation about users (or as often referred to herein,“participants”), or may make use of personal information, the users maybe provided with an opportunity to control whether programs or featurescollect user information (e.g., information about a user's socialnetwork, social actions or activities, profession, a user's preferences,or a user's current geographic location), or to control whether and/orhow to receive content from the content server that may be more relevantto the user. Also, certain data may be treated in one or more waysbefore it is stored or used, so that personal identifiable informationis removed. For example, a user's identity may be treated so that nopersonal identifiable information can be determined for the user, or auser's geographic location may be generalized where geographic locationinformation is obtained (such as to a city, ZIP code, or state level),so that a particular geographic location of a user cannot be determined.Thus, the user may have control over how information is collected aboutthe user and/or used.

While several implementations have been described and illustratedherein, a variety of other means and/or structures for performing thefunction and/or obtaining the results and/or one or more of theadvantages described herein may be utilized, and each of such variationsand/or modifications is deemed to be within the scope of theimplementations described herein. More generally, all parameters,dimensions, materials, and configurations described herein are meant tobe exemplary and that the actual parameters, dimensions, materials,and/or configurations will depend upon the specific application orapplications for which the teachings is/are used. Those skilled in theart will recognize, or be able to ascertain using no more than routineexperimentation, many equivalents to the specific implementationsdescribed herein. It is, therefore, to be understood that the foregoingimplementations are presented by way of example only and that, withinthe scope of the appended claims and equivalents thereto,implementations may be practiced otherwise than as specificallydescribed and claimed. Implementations of the present disclosure aredirected to each individual feature, system, article, material, kit,and/or method described herein. In addition, any combination of two ormore such features, systems, articles, materials, kits, and/or methods,if such features, systems, articles, materials, kits, and/or methods arenot mutually inconsistent, is included within the scope of the presentdisclosure.

We claim:
 1. A method implemented by one or more processors, the methodcomprising: receiving, at an automated assistant interface of anautomated assistant, a spoken utterance provided by a user while theuser is awake; determining, based on processing the spoken utterance,that the spoken utterance includes a request to initialize playback ofmedia in accordance with a desired condition of a dynamic condition ofthe user and further includes an indication from the user that the userhas an intention to change the dynamic condition of the user from aninitial condition to the desired condition; determining an initial valueof the initial condition of the dynamic condition of the user, where theinitial value of the initial condition of the dynamic condition isdetected at the time the user provided the spoken utterance while theuser is awake; determining a present value, of an adjustablecharacteristic of the playback of media, based on the initial value ofthe initial condition of the dynamic condition of the user in which theuser provided the spoken utterance; in response to determining that thespoken utterance includes the request to initialize the playback ofmedia, causing a computing device to render the playback of media basedon the present value of the adjustable characteristic of the playback ofmedia; after initializing the playback of the media: processing datathat is based on one or more sensors in an environment to determine acurrent condition of the dynamic condition of the user; determining,based on the processing of the data, whether the present value, of theadjustable characteristic of the playback of media which is based on thedynamic condition of the user, is unsuitable for the current conditionof the user, wherein the current condition corresponds to the desiredcondition of the user; wherein determining whether the present value isunsuitable for the current condition of the user is based on whether thepresent value will increase a probability that the user will regressaway from the desired condition of the user and towards the initialcondition; and when the present value is determined to be unsuitable forthe current condition of the user; selecting an alternate value for theadjustable characteristic of the playback of media, wherein theselecting the alternate value is based on a change in the value of thedynamic condition of the user from the initial value to a current valueindicative of the current condition of the user, wherein the alternatevalue is selected to decrease the probability of the user regressingaway from the desired condition of the user and towards the initialcondition, and causing the computing device to transition the playbackof media from exhibiting the present value to the alternate, value. 2.The method of claim 1, wherein the present value of the playback ofmedia corresponds to a volume of the playback of media being emittedinto the environment, and wherein the alternate value of the playback ofmedia corresponds to a lower volume of the playback of media, the lowervolume of the playback of media being lower relative to the volume ofthe present value of the playback of media.
 3. The method of claim 1,further comprising: determining whether the present value of theplayback of media will increase the probability that the user willregress away from the desired condition further based on acorrespondence between the current condition of the user and the presentvalue of the playback of media.
 4. The method of claim 1, wherein theone or more sensors in the environment, on which the data is based,comprise a sensor that is attached to a wearable computing device beingworn by the user.
 5. The method of claim 1, wherein the one or moresensors are responsive to physiological attributes of the user, andwherein the dynamic condition of the user is based on the physiologicalattributes of the user and the desired condition of the user is a sleepstate.
 6. The method of claim 1, wherein the data includescircumstantial data that is based on outputs from multiple differentcomputing devices connected to a local area network with the computingdevice.
 7. The method of claim 1, wherein the initial condition is basedon an amplitude of the spoken utterance.
 8. A non-transitory computerreadable storage medium configured to store instructions that, whenexecuted by one or more processors, cause the one or more processors toperform operations that include: receiving, at an automated assistantinterface of an automated assistant, a spoken utterance provided by auser while the user is awake; determining, based on processing thespoken utterance, that the spoken utterance includes a request toinitialize playback of media in accordance with a desired condition of adynamic condition of the user and further includes an indication fromthe user that the user has an intention to change the dynamic conditionof the user from an initial condition to the desired condition;determining an initial value of the initial condition of the dynamiccondition of the user, where the initial value of the initial conditionof the dynamic condition is detected at the time the user provided thespoken utterance while the user is awake; determining a present value,of an adjustable characteristic of the playback of media, based on theinitial value of the initial condition of the dynamic condition of theuser in which the user provided the spoken utterance; in response todetermining that the spoken utterance includes the request to initializethe playback of media, causing a computing device, to render theplayback of media based on the present value of the adjustablecharacteristic of the playback of media; after initializing the playbackof the media: processing data that is based on one or more sensors in anenvironment to determine a current condition of the dynamic condition ofthe user: determining, based on the processing of the data, whether thepresent value, of the adjustable characteristic of the playback of mediawhich is based on the dynamic condition of the user, is unsuitable forthe current condition of the user, wherein the current conditioncorresponds to the desired condition of the user; wherein determiningwhether the present value is unsuitable for the current condition of theuser is based on whether the present value will increase a probabilitythat the user will regress away from the desired condition of the userand towards the initial condition; and when the present value isdetermined to be unsuitable for the current condition of the user:selecting an alternate value for the adjustable characteristic of theplayback of media, wherein the selecting the alternate value is based ona change in the value of the dynamic condition of the user from theinitial value to a current value indicative of the current condition ofthe user, Wherein the alternate value is selected to decrease theprobability of the user regressing away from the desired condition ofthe user and towards the initial condition, and causing the computingdevice to transition the playback of media from exhibiting the presentvalue to the alternate value.
 9. The non-transitory computer readablestorage medium of claim 8, wherein the present value of the playback ofmedia corresponds to a volume of the media being emitted into theenvironment, and wherein the alternate value of the playback of mediacorresponds to a lower volume of the playback of media, the lower volumeof the playback of media being lower relative to the volume of thepresent value of the playback of media.
 10. The non-transitory computerreadable storage medium of claim 8, wherein the operations furtherinclude: determining whether the present value of the playback of mediawill increase the probability that the user will regress away from thedesired condition further based on a correspondence between the currentcondition of the user and the present value of the playback of media.11. The non-transitory computer readable storage medium of claim 8,wherein the one or more sensors in the environment, on which the data isbased, comprise a sensor that is integral to a wearable computing devicebeing worn by the user.
 12. The non-transitory computer readable storagemedium of claim 11, wherein the one or more sensors are responsive tophysiological attributes of the user, and wherein the dynamic conditionof the user is based on the physiological attributes of the user and thedesired condition of the user is a sleep state.
 13. The non-transitorycomputer readable storage medium of claim 8, wherein the data includescircumstantial data that is based on outputs from multiple differentcomputing devices connected to a local area network with the computingdevice.
 14. A computing device, comprising one or more processors, andmemory configured to store instructions that, when executed by the oneor more processors, cause the one or more processors to performoperations that include: receiving, at an automated assistant interfaceof an automated assistant, a spoken utterance provided by a user whilethe user is awake; determining, based on processing the spokenutterance, that the spoken utterance includes a request to initializeplayback of media in accordance with a desired condition of a dynamiccondition of the user and further includes an indication from the userthat the user has an intention to change the dynamic condition of theuser from an initial condition to the desired condition; determining aninitial value of the initial condition of the dynamic condition of theuser, where the initial value of the initial condition of the dynamiccondition is detected at the time the user provided the spoken utterancewhile the user is awake determining a present value, of an adjustablecharacteristic of the playback of media, based on the initial value ofthe initial condition of the dynamic condition of the user in Which theuser provided the spoken utterance; in response to determining that thespoken utterance includes the request to initialize, the playback ofmedia, causing a computing device to render the playback of media basedon the present value of the adjustable characteristic of the playback ofmedia; after initializing the playback of the media: processing datathat is based on one or more sensors in an environment to determine acurrent condition of the dynamic condition of the user: determining,based on the processing of the data, whether the present value, of theadjustable characteristic of the playback of media which is based on thedynamic condition of the user, is unsuitable for the current conditionof the user, wherein the current condition corresponds to the desiredcondition of the user; wherein determining whether the present value isunsuitable for the current condition of the user is based on whether thepresent value will increase a probability that the user will regressaway from the desired condition of the user and towards the initialcondition; and when the present value is determined to be unsuitable forthe current condition of the user: selecting an alternate value for theadjustable characteristic of the playback of media, wherein theselecting the alternate value is based on a change in the value of thedynamic condition of the user from the initial value to a current valueindicative of the current condition of the user, wherein the alternatevalue is selected to decrease the probability of the user regressingaway from the desired condition of the user and towards the initialcondition, and causing the computing device to transition the playbackof media from exhibiting the present value to the alternate value. 15.The computing device of claim 14, wherein the operations furtherinclude: determining whether the present value of the playback of mediawill increase the probability that the user will regress away from thedesired condition further based on a correspondence between the currentcondition of the user and the present value of the playback of media.16. The computing device of claim 14, wherein the one or more sensors inthe environment, on which the data is based, comprise a sensor that isintegral to a wearable computing device being worn by the user.
 17. Thecomputing device of claim 14, wherein the one or more sensors areresponsive to physiological attributes of the user, and wherein thedynamic condition of the user is based on the physiological attributesof the user and the desired condition of the user is a sleep state.